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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_surveyscores.wasp
Title produced by softwareSurvey Scores
Date of computationTue, 18 Oct 2011 06:15:52 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Oct/18/t131893297033f6v910vz1ykdu.htm/, Retrieved Thu, 31 Oct 2024 23:28:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=131627, Retrieved Thu, 31 Oct 2024 23:28:15 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact107
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Survey Scores] [Intrinsic Motivat...] [2010-10-12 11:18:40] [b98453cac15ba1066b407e146608df68]
- R PD    [Survey Scores] [WS3, Q1] [2011-10-18 10:15:52] [13d85cac30d4a10947636c080219d4f4] [Current]
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Dataseries X:
4	7	7	6	1	5	7	7	7	7	6	1	7	1	5	7	4	4	1	4	4	7	5	5	5	1	5	5
5	5	6	4	1	4	5	5	5	6	4	1	4	3	5	5	6	3	1	4	5	5	5	6	4	1	4	4
4	6	6	6	2	5	5	6	5	6	2	1	4	4	5	4	5	5	1	5	4	5	4	5	5	2	5	5
3	4	5	4	2	4	5	6	5	6	2	2	4	5	6	5	4	2	2	5	5	6	5	5	3	2	5	6
6	5	6	2	2	4	5	6	5	6	2	2	4	5	6	5	6	2	2	4	5	6	5	6	2	2	4	5
5	6	7	5	1	6	7	5	6	7	5	1	6	7	5	6	6	5	1	6	7	7	7	7	4	1	5	7
5	7	7	1	1	5	7	7	4	7	1	1	4	1	5	7	7	1	1	4	4	6	7	7	1	1	4	7
1	6	7	6	1	3	5	6	5	7	4	1	2	5	6	5	6	5	4	2	6	7	6	7	5	2	5	6
4	6	7	3	1	4	3	7	7	6	5	2	6	2	7	7	5	4	1	5	4	7	6	6	4	1	4	7
5	6	6	4	1	4	6	6	5	6	4	1	3	3	6	5	5	3	1	5	3	6	6	6	3	1	4	6
6	5	4	3	1	2	7	7	2	7	1	1	6	6	7	4	7	1	1	5	5	7	6	6	5	1	6	7
7	5	6	2	1	5	6	7	5	7	2	1	5	4	6	6	7	5	1	6	2	7	6	7	4	1	4	5
5	4	6	4	1	3	5	6	5	7	4	1	4	3	6	4	7	3	1	3	3	5	6	7	3	1	3	3
6	6	7	3	1	5	3	6	6	7	2	1	5	3	6	6	7	2	1	5	3	6	6	7	1	1	5	2
5	6	6	5	1	6	7	7	6	7	6	1	7	6	6	7	7	6	1	7	7	7	7	7	6	1	7	7
4	5	6	3	2	4	5	6	5	6	3	3	4	5	6	6	6	3	2	5	5	6	5	5	2	1	4	5
7	3	4	3	1	3	7	7	3	7	2	1	1	5	7	4	6	2	1	2	5	7	3	7	2	1	2	5
7	7	7	6	1	6	7	7	6	7	6	1	6	5	7	6	7	6	1	7	4	7	7	7	6	1	6	6
6	3	7	1	1	7	7	7	5	7	2	1	7	1	7	6	7	1	1	5	6	7	6	6	1	1	7	7
6	5	6	1	2	2	6	7	5	7	6	2	4	5	6	6	6	4	2	3	6	6	6	6	4	2	4	6
2	3	3	1	1	6	5	5	3	5	1	1	5	3	5	4	5	1	1	3	4	4	4	6	2	1	5	5
7	5	7	5	1	4	7	7	5	4	4	4	4	4	7	5	7	5	1	1	6	7	6	6	5	1	6	7
5	2	5	2	1	1	4	5	1	6	1	1	1	2	5	2	5	1	1	2	3	6	2	4	2	1	1	5
4	6	7	3	1	4	7	6	5	7	4	1	4	3	7	6	7	3	1	5	2	7	6	7	3	1	3	5
7	3	6	3	1	3	7	7	4	7	2	2	2	5	6	5	6	2	1	5	5	7	5	7	4	1	4	6
1	6	5	5	1	6	7	6	6	7	5	1	6	5	2	6	6	6	1	7	5	5	7	5	1	1	5	7
1	6	5	5	1	6	7	6	6	7	5	1	6	5	2	6	6	6	1	7	5	5	7	5	1	1	5	7
7	5	6	1	1	3	3	6	4	6	1	1	3	2	7	5	2	1	1	2	1	7	5	6	2	1	1	2
4	5	5	2	1	6	7	6	4	2	1	1	5	4	4	5	2	2	1	4	5	6	6	2	4	1	4	6
5	7	6	3	1	4	5	6	5	6	4	1	5	6	4	5	5	4	1	5	6	6	6	7	4	1	5	6
5	6	6	5	1	7	7	6	4	7	4	1	6	6	5	6	6	4	1	6	5	6	6	6	4	1	6	7
5	5	5	3	1	4	5	5	5	6	5	1	5	4	5	6	6	4	1	5	6	6	6	6	5	1	5	6
4	5	4	5	4	4	5	3	6	4	5	6	4	6	4	5	4	4	3	5	7	1	5	6	6	2	5	6
5	4	5	3	3	3	4	3	3	5	3	3	4	3	7	4	4	3	3	4	4	5	4	6	3	1	4	4
5	4	4	2	1	4	5	5	5	5	1	1	1	6	7	6	5	1	1	3	5	7	5	6	3	1	4	6
4	6	6	4	2	6	6	6	5	6	5	2	5	3	4	5	6	3	2	6




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=131627&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=131627&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=131627&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Summary of survey scores (median of Likert score was subtracted)
QuestionmeanSum ofpositives (Ps)Sum ofnegatives (Ns)(Ps-Ns)/(Ps+Ns)Count ofpositives (Pc)Count ofnegatives (Nc)(Pc-Nc)/(Pc+Nc)
10.7840120.542350.64
21.144760.772750.69
31.786510.973110.94
4-0.561535-0.41120-0.29
5-2.69097-1035-1
60.3927130.351590.25
71.726530.913130.82
827420.953420.89
90.813780.642650.68
102.198120.953310.94
11-0.671539-0.441117-0.21
12-2.5292-0.96134-0.94
130.4230150.331770.42
140.0625230.0417140.1
151.586140.883020.88
161.335020.922910.93
171.646340.883020.88
18-0.751340-0.51920-0.38
19-2.67096-1035-1
200.533150.382190.4
210.6133110.52170.5
222.087830.933410.94
231.586030.93120.88
2427420.953410.94
25-0.671236-0.5918-0.33
26-2.72199-0.98135-0.94
270.5329100.491950.58
281.646450.863130.82

\begin{tabular}{lllllllll}
\hline
Summary of survey scores (median of Likert score was subtracted) \tabularnewline
Question & mean & Sum ofpositives (Ps) & Sum ofnegatives (Ns) & (Ps-Ns)/(Ps+Ns) & Count ofpositives (Pc) & Count ofnegatives (Nc) & (Pc-Nc)/(Pc+Nc) \tabularnewline
1 & 0.78 & 40 & 12 & 0.54 & 23 & 5 & 0.64 \tabularnewline
2 & 1.14 & 47 & 6 & 0.77 & 27 & 5 & 0.69 \tabularnewline
3 & 1.78 & 65 & 1 & 0.97 & 31 & 1 & 0.94 \tabularnewline
4 & -0.56 & 15 & 35 & -0.4 & 11 & 20 & -0.29 \tabularnewline
5 & -2.69 & 0 & 97 & -1 & 0 & 35 & -1 \tabularnewline
6 & 0.39 & 27 & 13 & 0.35 & 15 & 9 & 0.25 \tabularnewline
7 & 1.72 & 65 & 3 & 0.91 & 31 & 3 & 0.82 \tabularnewline
8 & 2 & 74 & 2 & 0.95 & 34 & 2 & 0.89 \tabularnewline
9 & 0.81 & 37 & 8 & 0.64 & 26 & 5 & 0.68 \tabularnewline
10 & 2.19 & 81 & 2 & 0.95 & 33 & 1 & 0.94 \tabularnewline
11 & -0.67 & 15 & 39 & -0.44 & 11 & 17 & -0.21 \tabularnewline
12 & -2.5 & 2 & 92 & -0.96 & 1 & 34 & -0.94 \tabularnewline
13 & 0.42 & 30 & 15 & 0.33 & 17 & 7 & 0.42 \tabularnewline
14 & 0.06 & 25 & 23 & 0.04 & 17 & 14 & 0.1 \tabularnewline
15 & 1.58 & 61 & 4 & 0.88 & 30 & 2 & 0.88 \tabularnewline
16 & 1.33 & 50 & 2 & 0.92 & 29 & 1 & 0.93 \tabularnewline
17 & 1.64 & 63 & 4 & 0.88 & 30 & 2 & 0.88 \tabularnewline
18 & -0.75 & 13 & 40 & -0.51 & 9 & 20 & -0.38 \tabularnewline
19 & -2.67 & 0 & 96 & -1 & 0 & 35 & -1 \tabularnewline
20 & 0.5 & 33 & 15 & 0.38 & 21 & 9 & 0.4 \tabularnewline
21 & 0.61 & 33 & 11 & 0.5 & 21 & 7 & 0.5 \tabularnewline
22 & 2.08 & 78 & 3 & 0.93 & 34 & 1 & 0.94 \tabularnewline
23 & 1.58 & 60 & 3 & 0.9 & 31 & 2 & 0.88 \tabularnewline
24 & 2 & 74 & 2 & 0.95 & 34 & 1 & 0.94 \tabularnewline
25 & -0.67 & 12 & 36 & -0.5 & 9 & 18 & -0.33 \tabularnewline
26 & -2.72 & 1 & 99 & -0.98 & 1 & 35 & -0.94 \tabularnewline
27 & 0.53 & 29 & 10 & 0.49 & 19 & 5 & 0.58 \tabularnewline
28 & 1.64 & 64 & 5 & 0.86 & 31 & 3 & 0.82 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=131627&T=1

[TABLE]
[ROW][C]Summary of survey scores (median of Likert score was subtracted)[/C][/ROW]
[ROW][C]Question[/C][C]mean[/C][C]Sum ofpositives (Ps)[/C][C]Sum ofnegatives (Ns)[/C][C](Ps-Ns)/(Ps+Ns)[/C][C]Count ofpositives (Pc)[/C][C]Count ofnegatives (Nc)[/C][C](Pc-Nc)/(Pc+Nc)[/C][/ROW]
[ROW][C]1[/C][C]0.78[/C][C]40[/C][C]12[/C][C]0.54[/C][C]23[/C][C]5[/C][C]0.64[/C][/ROW]
[ROW][C]2[/C][C]1.14[/C][C]47[/C][C]6[/C][C]0.77[/C][C]27[/C][C]5[/C][C]0.69[/C][/ROW]
[ROW][C]3[/C][C]1.78[/C][C]65[/C][C]1[/C][C]0.97[/C][C]31[/C][C]1[/C][C]0.94[/C][/ROW]
[ROW][C]4[/C][C]-0.56[/C][C]15[/C][C]35[/C][C]-0.4[/C][C]11[/C][C]20[/C][C]-0.29[/C][/ROW]
[ROW][C]5[/C][C]-2.69[/C][C]0[/C][C]97[/C][C]-1[/C][C]0[/C][C]35[/C][C]-1[/C][/ROW]
[ROW][C]6[/C][C]0.39[/C][C]27[/C][C]13[/C][C]0.35[/C][C]15[/C][C]9[/C][C]0.25[/C][/ROW]
[ROW][C]7[/C][C]1.72[/C][C]65[/C][C]3[/C][C]0.91[/C][C]31[/C][C]3[/C][C]0.82[/C][/ROW]
[ROW][C]8[/C][C]2[/C][C]74[/C][C]2[/C][C]0.95[/C][C]34[/C][C]2[/C][C]0.89[/C][/ROW]
[ROW][C]9[/C][C]0.81[/C][C]37[/C][C]8[/C][C]0.64[/C][C]26[/C][C]5[/C][C]0.68[/C][/ROW]
[ROW][C]10[/C][C]2.19[/C][C]81[/C][C]2[/C][C]0.95[/C][C]33[/C][C]1[/C][C]0.94[/C][/ROW]
[ROW][C]11[/C][C]-0.67[/C][C]15[/C][C]39[/C][C]-0.44[/C][C]11[/C][C]17[/C][C]-0.21[/C][/ROW]
[ROW][C]12[/C][C]-2.5[/C][C]2[/C][C]92[/C][C]-0.96[/C][C]1[/C][C]34[/C][C]-0.94[/C][/ROW]
[ROW][C]13[/C][C]0.42[/C][C]30[/C][C]15[/C][C]0.33[/C][C]17[/C][C]7[/C][C]0.42[/C][/ROW]
[ROW][C]14[/C][C]0.06[/C][C]25[/C][C]23[/C][C]0.04[/C][C]17[/C][C]14[/C][C]0.1[/C][/ROW]
[ROW][C]15[/C][C]1.58[/C][C]61[/C][C]4[/C][C]0.88[/C][C]30[/C][C]2[/C][C]0.88[/C][/ROW]
[ROW][C]16[/C][C]1.33[/C][C]50[/C][C]2[/C][C]0.92[/C][C]29[/C][C]1[/C][C]0.93[/C][/ROW]
[ROW][C]17[/C][C]1.64[/C][C]63[/C][C]4[/C][C]0.88[/C][C]30[/C][C]2[/C][C]0.88[/C][/ROW]
[ROW][C]18[/C][C]-0.75[/C][C]13[/C][C]40[/C][C]-0.51[/C][C]9[/C][C]20[/C][C]-0.38[/C][/ROW]
[ROW][C]19[/C][C]-2.67[/C][C]0[/C][C]96[/C][C]-1[/C][C]0[/C][C]35[/C][C]-1[/C][/ROW]
[ROW][C]20[/C][C]0.5[/C][C]33[/C][C]15[/C][C]0.38[/C][C]21[/C][C]9[/C][C]0.4[/C][/ROW]
[ROW][C]21[/C][C]0.61[/C][C]33[/C][C]11[/C][C]0.5[/C][C]21[/C][C]7[/C][C]0.5[/C][/ROW]
[ROW][C]22[/C][C]2.08[/C][C]78[/C][C]3[/C][C]0.93[/C][C]34[/C][C]1[/C][C]0.94[/C][/ROW]
[ROW][C]23[/C][C]1.58[/C][C]60[/C][C]3[/C][C]0.9[/C][C]31[/C][C]2[/C][C]0.88[/C][/ROW]
[ROW][C]24[/C][C]2[/C][C]74[/C][C]2[/C][C]0.95[/C][C]34[/C][C]1[/C][C]0.94[/C][/ROW]
[ROW][C]25[/C][C]-0.67[/C][C]12[/C][C]36[/C][C]-0.5[/C][C]9[/C][C]18[/C][C]-0.33[/C][/ROW]
[ROW][C]26[/C][C]-2.72[/C][C]1[/C][C]99[/C][C]-0.98[/C][C]1[/C][C]35[/C][C]-0.94[/C][/ROW]
[ROW][C]27[/C][C]0.53[/C][C]29[/C][C]10[/C][C]0.49[/C][C]19[/C][C]5[/C][C]0.58[/C][/ROW]
[ROW][C]28[/C][C]1.64[/C][C]64[/C][C]5[/C][C]0.86[/C][C]31[/C][C]3[/C][C]0.82[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=131627&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=131627&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of survey scores (median of Likert score was subtracted)
QuestionmeanSum ofpositives (Ps)Sum ofnegatives (Ns)(Ps-Ns)/(Ps+Ns)Count ofpositives (Pc)Count ofnegatives (Nc)(Pc-Nc)/(Pc+Nc)
10.7840120.542350.64
21.144760.772750.69
31.786510.973110.94
4-0.561535-0.41120-0.29
5-2.69097-1035-1
60.3927130.351590.25
71.726530.913130.82
827420.953420.89
90.813780.642650.68
102.198120.953310.94
11-0.671539-0.441117-0.21
12-2.5292-0.96134-0.94
130.4230150.331770.42
140.0625230.0417140.1
151.586140.883020.88
161.335020.922910.93
171.646340.883020.88
18-0.751340-0.51920-0.38
19-2.67096-1035-1
200.533150.382190.4
210.6133110.52170.5
222.087830.933410.94
231.586030.93120.88
2427420.953410.94
25-0.671236-0.5918-0.33
26-2.72199-0.98135-0.94
270.5329100.491950.58
281.646450.863130.82







Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.98 (0)0.985 (0)
(Ps-Ns)/(Ps+Ns)0.98 (0)1 (0)0.995 (0)
(Pc-Nc)/(Pc+Nc)0.985 (0)0.995 (0)1 (0)

\begin{tabular}{lllllllll}
\hline
Pearson correlations of survey scores (and p-values) \tabularnewline
 & mean & (Ps-Ns)/(Ps+Ns) & (Pc-Nc)/(Pc+Nc) \tabularnewline
mean & 1 (0) & 0.98 (0) & 0.985 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.98 (0) & 1 (0) & 0.995 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.985 (0) & 0.995 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=131627&T=2

[TABLE]
[ROW][C]Pearson correlations of survey scores (and p-values)[/C][/ROW]
[ROW][C][/C][C]mean[/C][C](Ps-Ns)/(Ps+Ns)[/C][C](Pc-Nc)/(Pc+Nc)[/C][/ROW]
[ROW][C]mean[/C][C]1 (0)[/C][C]0.98 (0)[/C][C]0.985 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.98 (0)[/C][C]1 (0)[/C][C]0.995 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.985 (0)[/C][C]0.995 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=131627&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=131627&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.98 (0)0.985 (0)
(Ps-Ns)/(Ps+Ns)0.98 (0)1 (0)0.995 (0)
(Pc-Nc)/(Pc+Nc)0.985 (0)0.995 (0)1 (0)







Kendall tau rank correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.9 (0)0.889 (0)
(Ps-Ns)/(Ps+Ns)0.9 (0)1 (0)0.936 (0)
(Pc-Nc)/(Pc+Nc)0.889 (0)0.936 (0)1 (0)

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations of survey scores (and p-values) \tabularnewline
 & mean & (Ps-Ns)/(Ps+Ns) & (Pc-Nc)/(Pc+Nc) \tabularnewline
mean & 1 (0) & 0.9 (0) & 0.889 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.9 (0) & 1 (0) & 0.936 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.889 (0) & 0.936 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=131627&T=3

[TABLE]
[ROW][C]Kendall tau rank correlations of survey scores (and p-values)[/C][/ROW]
[ROW][C][/C][C]mean[/C][C](Ps-Ns)/(Ps+Ns)[/C][C](Pc-Nc)/(Pc+Nc)[/C][/ROW]
[ROW][C]mean[/C][C]1 (0)[/C][C]0.9 (0)[/C][C]0.889 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.9 (0)[/C][C]1 (0)[/C][C]0.936 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.889 (0)[/C][C]0.936 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=131627&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=131627&T=3

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The GUIDs for individual cells are displayed in the table below:

Kendall tau rank correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.9 (0)0.889 (0)
(Ps-Ns)/(Ps+Ns)0.9 (0)1 (0)0.936 (0)
(Pc-Nc)/(Pc+Nc)0.889 (0)0.936 (0)1 (0)



Parameters (Session):
par1 = 1 2 3 4 5 6 7 ;
Parameters (R input):
par1 = 1 2 3 4 5 6 7 ;
R code (references can be found in the software module):
docor <- function(x,y,method) {
r <- cor.test(x,y,method=method)
paste(round(r$estimate,3),' (',round(r$p.value,3),')',sep='')
}
x <- t(x)
nx <- length(x[,1])
cx <- length(x[1,])
mymedian <- median(as.numeric(strsplit(par1,' ')[[1]]))
myresult <- array(NA, dim = c(cx,7))
rownames(myresult) <- paste('Q',1:cx,sep='')
colnames(myresult) <- c('mean','Sum of
positives (Ps)','Sum of
negatives (Ns)', '(Ps-Ns)/(Ps+Ns)', 'Count of
positives (Pc)', 'Count of
negatives (Nc)', '(Pc-Nc)/(Pc+Nc)')
for (i in 1:cx) {
spos <- 0
sneg <- 0
cpos <- 0
cneg <- 0
for (j in 1:nx) {
if (!is.na(x[j,i])) {
myx <- as.numeric(x[j,i]) - mymedian
if (myx > 0) {
spos = spos + myx
cpos = cpos + 1
}
if (myx < 0) {
sneg = sneg + abs(myx)
cneg = cneg + 1
}
}
}
myresult[i,1] <- round(mean(as.numeric(x[,i]),na.rm=T)-mymedian,2)
myresult[i,2] <- spos
myresult[i,3] <- sneg
myresult[i,4] <- round((spos - sneg) / (spos + sneg),2)
myresult[i,5] <- cpos
myresult[i,6] <- cneg
myresult[i,7] <- round((cpos - cneg) / (cpos + cneg),2)
}
myresult
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Summary of survey scores (median of Likert score was subtracted)',8,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Question',header=TRUE)
for (i in 1:7) {
a<-table.element(a,colnames(myresult)[i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:cx) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
for (j in 1:7) {
a<-table.element(a,myresult[i,j],align='right')
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Pearson correlations of survey scores (and p-values)',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,docor(myresult[,1],myresult[,1],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,4],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,7],method='pearson'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,docor(myresult[,4],myresult[,1],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,4],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,7],method='pearson'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.element(a,docor(myresult[,7],myresult[,1],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,4],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,7],method='pearson'),align='right')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Kendall tau rank correlations of survey scores (and p-values)',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,docor(myresult[,1],myresult[,1],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,4],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,7],method='kendall'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,docor(myresult[,4],myresult[,1],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,4],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,7],method='kendall'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.element(a,docor(myresult[,7],myresult[,1],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,4],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,7],method='kendall'),align='right')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')